NeTS: Small: Collaborative Research: Supporting unstructured peer-to-peer social networking

NetS：小型：协作研究：支持非结构化点对点社交网络

• 批准号: 0915928
• 负责人: Gustavo de Veciana
• 金额: $ 15万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0915928&HistoricalAwards=false
• 关键词: NeTS; Small; Collaborative; Research; Supporting

0915928 - NeTS: Small: Collaborative Research: Supporting unstructured peer-to-peer social networking09/01/09-08/31/12G. de Veciana, PI, U.T. Austin, and G. Kesidis, PI, Penn StateAward Abstract:Peer-to-peer systems have seen continued growth, in terms of traffic volume, and as the architecture of choice to build new applications and network services ? notable benefits lie in their distributed design leading to higher reliability and flexibility. However as users/peers increasingly become content providers, and generally conduct more of their business on the network, privacy is a critical concern.By leveraging peers? trust relationships through referral mechanisms based on underlying reputation systems, applications that deliver a new standard of privacy are being devised. Peer-to-peer systems that dynamically adapt, in a distributed and scalable manner, based on the outcomes of peer transactions, are being modeled and analyzed. The focus is on unstructured networks where peer-membership correlations among communities of interest can be learned to improve the search performance of reputation-biased random walks and limited-scope flooding. Content-sharing applications are being designed based that leverage this framework to incentivize cooperative behavior while enabling collaborative filtering and content pushing.Expected results include the development analysis and testing of a new framework for privacy-preserving search for large-scale, unstructured, on-line, peer-to-peer networks. Complementary incentive mechanisms resulting in improve file sharing and promoting honest referrals will be devised. The results will be disseminated through peer-reviewed venues and, where possible, industry concerns, while data and simulation tools are made available on the web.The efforts impact will lie in contributing new ways to improve privacy and promote more honest and efficient cooperation in large-scale on-line peer-to-peer systems, for content sharing, as well as a broader set of social networking applications.

0915928 -NetTS：小：协作研究：支持非结构化对等社交网络09/01/09-08/31/12 G。de Veciana，PI，U.T. Austin和G. Kesidis，PI，宾夕法尼亚州立大学奖摘要：对等系统已经看到了持续增长，在流量方面，并作为选择的架构，以建立新的应用程序和网络服务？值得注意的好处在于其分布式设计， 可靠性和灵活性。然而，随着用户/对等体越来越多地成为内容提供者，并且通常在网络上进行更多的业务，隐私是一个关键问题。通过基于基本信誉系统的转介机制建立信任关系，正在设计提供新的隐私标准的应用程序。对等系统的动态适应，在一个分布式和可扩展的方式，基于对等事务的结果，正在建模和分析。重点是非结构化网络，其中可以学习感兴趣的社区之间的对等成员关系，以提高声誉偏置随机游走和有限范围洪泛的搜索性能。内容共享应用程序正在设计的基础上，利用这个框架，以激励合作行为，同时使协同过滤和内容pushing.Expected结果包括开发分析和测试的一个新的框架，隐私保护搜索的大规模，非结构化，在线，对等网络。将制定补充激励机制，以改善档案共享和促进诚实的转介。研究结果将通过同行审查的渠道传播，并在可能的情况下通过行业关注点传播，同时在网上提供数据和模拟工具，其影响将在于提出新的方法，以改善隐私，促进在大规模在线对等系统中进行更诚实和有效的合作，以实现内容共享，以及更广泛的社交网络应用。